A new computer model to predict the weather built by Google and powered by artificial intelligence consistently outperforms and is many times faster than government models that have existed for decades and involved hundreds of millions of dollars in investment, according to a study published Tuesday.
The Google model even displayed accuracy superior to the “European model,” widely considered the gold standard.
The study, published in the journal Science, showed the AI model to be more accurate for forecasts of both day-to-day weather and extreme events, such as hurricanes and intense heat and cold.
Its stellar performance and promising results from other AI models like it may signify the start of a new era for weather prediction, although experts say it doesn’t mean AI is ready to replace all traditional forecasting methods.
Google DeepMind’s AI model, named “GraphCast,” was trained on nearly 40 years of historical data and can make a 10-day forecast at six-hour intervals for locations spread around the globe in less than a minute on a computer the size of a small box.
It takes a traditional model an hour or more on a supercomputer the size of a school bus to accomplish the same feat. GraphCast was about 10 percent more accurate than the European model on more than 90 percent of the weather variables evaluated.
The study’s results are similar to those in an academic article published in August in the online database arXiv.
“To be competitive with arguably the best global prediction system, if not outperforming it, is astonishing,” Aaron Hill, lead developer of Colorado State University’s machine learning prediction system, said in an email. “You can safely add GraphCast to a growing list of AI-based weather prediction models that should see continued evaluation for their application in industry, research and operational forecasting.”